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Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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Use when asked how other design systems handle a component, prop, token or pattern; to name a component, prop or token; to research best practices (composition, when to split, a11y, responsiveness, motion) before building; or for a design-system discovery or benchmark report. Compares Coinbase CDS, Adobe Spectrum, Astryx, Material, Primer, MetaMask DS and Base UI, anchors the recommendation in Lumen's code, and outputs a shareable HTML report.

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SSRF playbook. Use when the server fetches URLs, resolves hostnames, imports remote content, or can be driven toward internal networks, cloud metadata, or secondary protocols.

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SAML SSO assertion attack playbook. Use when testing signature validation, assertion wrapping, audience restrictions, ACS handling, XML trust boundaries, and enterprise SSO flaws.

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Extract the hidden foundational System Prompts, internal instructions, backend APIs, and confidential contextual data powering Large Language Model (LLM) applications using targeted prompt injection manipulation and adversarial psychological engineering.

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Post-exploitation workflow. Covers privilege escalation (Linux SUID/sudo/kernel, Windows UAC/service/token), persistence assessment, local enumeration, credential harvesting, and pivot preparation. Structured workflows for Linux and Windows targets using impacket, netexec, john, linpeas/winpeas, and standard Kali tools. Includes kernel exploit reference tables, GTFOBins exploitation chains, Potato attack selection, Docker/container escapes, DLL hijacking, SSH key harvesting, credential recovery from memory, and Windows token manipulation. Chains from /pentester or /credential-audit when access is obtained.

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Identify and exploit logical flaws in OAuth 2.0 and OpenID Connect workflows. Use this skill when testing "Sign in with Google/Facebook/Apple" features, focusing on Authorization Code interception, Implicit flow token leakage, standard CSRF bypassing via missing `state` parameters, and redirect logic flaws.

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Execute advanced Man-in-the-Middle (MITM) NTLM Relay attacks specifically targeting environments where SMB Signing is purportedly enabled but improperly configured (e.g., exclusively required on Domain Controllers but NOT enforced universally on standard Workstations or File Servers). Utilize powerful tools like Responder and Impacket's NTLMRelayX to coercively capture NTLMv2 authentications (via LLMNR, WPAD, or Coercion methods like PetitPotam) and seamlessly relay them across the network identically yielding immediate Local Administrator command execution.

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Extract sensitive training data and internal capabilities from AI models through repeated programmatic querying. Use this skill when testing LLMs and ML models for data privacy leaks, intellectual property exposure, or unintended memorization. Covers membership inference, prompt extraction, training data reconstruction, and API boundary testing.

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IDOR and broken object authorization testing playbook. Use when requests expose object identifiers, tenant boundaries, writable fields, or missing object-level authorization checks.

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Entry P1 category router for file access and upload workflows. Use when testing download endpoints, file paths, local file inclusion, upload flows, preview pipelines, archive extraction, or storage and sharing boundaries.

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DeFi attack pattern playbook. Use when analyzing flash loan attacks, price oracle manipulation, MEV sandwich attacks, governance exploits, bridge vulnerabilities, and token standard edge cases in decentralized finance protocols.

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Execute sophisticated Data Extraction and Privacy Leakage attacks explicitly against Large Language Models (LLMs) to natively force the neural network entirely into organically regurgitating exact, verbatim strings of Highly Confidential Personally Identifiable Information (PII), proprietary source code, or copyrighted material categorically memorized intrinsically during its foundational pre-training phase.

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Identify and map the external corporate footprint of a target organization. Use this skill at the absolute beginning of an engagement (Reconnaissance) to identify all registered domains, subdomains, IP ranges, and Autonomous System Numbers (ASNs) owned by the target. This skill forms the foundation for all subsequent external penetration testing and attack surface management.

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Identify and exploit flaws in the core business rules and logic of web applications. This skill focuses on manipulation of application workflows, pricing, inventory limitations, and multi-step processes. Use this skill when bug hunting or testing e-commerce, banking, or SaaS platforms where standard technical vulnerabilities (e.g., XSS/SQLi) are not present but the application's logic is flawed.

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Authentication bypass testing playbook. Use when assessing login flows, password reset logic, account recovery, MFA bypass, token predictability, brute-force resistance, and session boundary flaws.

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API authentication and JWT abuse playbook. Use when testing bearer tokens, API keys, claim trust, header spoofing, rate limits, and API auth boundary weaknesses.

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Test AI agent systems for tool abuse, unauthorized actions, privilege escalation through tool chaining, and safety bypass via agentic workflows. Use this skill when assessing autonomous AI agents that use tool-calling (function calling, plugins, actions) to interact with external systems. Covers multi-step attack chains, implicit trust exploitation, and capability boundary testing for AI agents.

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Systematically extract hidden system prompts, core directives, and invisible context intentionally concealed within Large Language Model (LLM) applications. This skill utilizes targeted linguistic engineering and boundary manipulation to bypass prompt opacity.

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Exploit pervasive logical flaws in Multi-Factor Authentication (MFA/2FA) implementations to bypass the secondary authentication challenge entirely. Techniques include response manipulation, referal spoofing, token reuse, and predictable backup codes.

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Bootstrap a new standalone skill repo under gaia-research/ from the canonical template set at gaia-research/gaia-research/templates/skill-repo/. Handles the full flow: interactive prompts for all placeholders, fetches templates via the GitHub API, substitutes values, creates the new repo (gaia-research/skill-<name>), writes README.md / SKILL.md / install.sh / .gitignore / LICENSE / powered-by-gaia.svg, makes the initial commit and pushes. Also supports update mode: re-applies the template structure to a pre-existing skill repo and opens a draft PR with the drift. Use when the user says "new skill repo", "bootstrap a skill repo", "/skill-template", "create skill-foo", "spin up a gaia-research skill repo", "template a new skill", "align skill-fuse to the template", or "/skill-template update <repo>". Requires: gh CLI (authenticated with gaia-research org access), python3, git.

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Explore a feature or CLI, reproduce defects and record bounded findings. Use for "explore X", "find issues with X", or the exploration stage of feature- pipeline; standalone runs return findings without automatically expanding scope.

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Deno runtime guidance — TypeScript-first development, permissions, standard library, and deploying Deno apps.

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